Surrogate Accelerated Bayesian Inversion for the Determination of the Thermal Diffusivity of a Material

Determination of the thermal properties of a material is an important task in many scientific and engineering applications. How a material behaves when subjected to high or fluctuating temperatures can be critical to the safety and longevity of a system's essential components. The laser flash experiment is a well-established technique for indirectly measuring the thermal diffusivity, and hence the thermal conductivity, of a material. In previous works, optimization schemes have been used to find estimates of the thermal conductivity and other quantities of interest which best fit a given model to experimental data. Adopting a Bayesian approach allows for prior beliefs about uncertain model inputs to be conditioned on experimental data to determine a posterior distribution, but probing this distribution using sampling techniques such as Markov chain Monte Carlo methods can be incredibly computationally intensive. This difficulty is especially true for forward models consisting of time-dependent partial differential equations. We pose the problem of determining the thermal conductivity of a material via the laser flash experiment as a Bayesian inverse problem in which the laser intensity is also treated as uncertain. We introduce a parametric surrogate model that takes the form of a stochastic Galerkin finite element approximation, also known as a generalized polynomial chaos expansion, and show how it can be used to sample efficiently from the approximate posterior distribution. This approach gives access not only to the sought-after estimate of the thermal conductivity but also important information about its relationship to the laser intensity, and information for uncertainty quantification. We also investigate the effects of the spatial profile of the laser on the estimated posterior distribution for the thermal conductivity

Conditions For Effective Use Of Community Sustainability Indicators And Adaptive Learning

Thesis (Ph.D.) University of Alaska Fairbanks, 2012As the number of community sustainability indicator programs (SIPs) increases in many regions of the world, including in the United States, questions continue to arise regarding how decision makers can use sustainability indicators (SIs) to contribute in a meaningful way to their efforts to build resilient and sustainable communities. Through an analysis of the sustainability activities in sample cities from across the U.S. and a case study of one city that adopted SIs but has yet to implement them, this study seeks to uncover the conditions for effective SI implementation and use. The study began with a review of the literature on communities' sustainability efforts and the historical roots of sustainability and resilience theory leading up to today's sustainability indicator projects. A heuristic model for adaptive learning is presented to illustrate the relationships among sustainability, resilience, and administrative concepts, including the goals and domains of sustainability indicators. The study's data collection and analysis began with an Internet-based investigation of 200 U.S. cities. A five-tiered system was devised to categorize findings regarding sustainability patterns and trends in studied cities, ranging from an absence of sustainability activities through fully implemented sustainability indicators. The second phase of data collection employed an electronic survey completed by informants from a 38-city sample of the 200 investigated cities, followed by phone interviews with informants from cities that ranked high for developed sustainability programs. A case study using focus group research was then conducted of one small U.S. city, Juneau, Alaska, where local government adopted sustainability indicators in the 1990s but fell short of implementing them. Most cities in the U.S. have not developed sustainability indicator projects, and, among those that have, few have been able to implement them fully. Among highly ranked cities with sustainability indicators, several approaches, including innovative organizational structures and adaptive learning processes, were found to be present. Recommendations for incorporating such innovations and for grounding sustainability indicator projects in sustainability science, resilience thinking, and public administration theory are offered to help ensure sustainability indicators become fully operational in Juneau, as well as in other communities seeking to establish successful sustainability indicator programs

Fourier domain diffuse correlation spectroscopy with heterodyne holographic detection

We present a new approach to diffuse correlation spectroscopy which overcomes the limited light throughput of single-mode photon counting techniques. Our system employs heterodyne holographic detection to allow parallel measurement of the power spectrum of a fluctuating electric field across thousands of modes, at the shot noise limit, using a conventional sCMOS camera. This yields an order of magnitude reduction in detector cost compared to conventional techniques, whilst also providing robustness to the effects of ambient light and an improved signal-to-noise ratio during in vitro experiments. We demonstrate a GPU-accelerated holographic demodulation system capable of processing the incoming data (79.4 M pixels per second) in real-time, and a novel Fourier domain model of diffuse correlation spectroscopy which permits the direct recovery of flow parameters from the measured data. Our detection and modelling strategy are rigorously validated by modulating the Brownian component of an optical tissue phantom, demonstrating absolute measurements of the Brownian diffusion coefficient in excellent agreement with conventional methods. We further demonstrate the feasibility of our system through in vivo measurement of pulsatile flow rates measured in the human forearm

Diffuse correlation spectroscopy in the Fourier domain with holographic camera-based detection

We present a new approach to Diffuse Correlation Spectroscopy (DCS) which overcomes the limited light throughput of single mode photon counting techniques, and operates with continuous wave illumination without disturbance from ambient light. Heterodyne holographic detection allows parallel measurement of the power spectrum of a fluctuating electric field across thousands of modes, from which we may directly compute flow parameters using a novel Fourier domain DCS model. Our detection and modelling strategy are rigorously validated by modulating the Brownian and flow components of an optical tissue phantom, demonstrating absolute measurements of the Brownian diffusion coefficient in excellent agreement with conventional methods. We demonstrate the feasability of in vivo measurement through the recovery of pulsatile flow rates measured in the human forearm

Editor\u27s Page

Message from the founding editors-in-chie

Editor\u27s Page

Message from the founding editors-in-chie

Simulation of time-integrated dynamic speckle patterns in biomedical optics

The simulation of statistically accurate 2D time-integrated dynamic speckle patterns using a model that accounts for spatially varying sample properties (such as scatterer motion and decorrelation time) is yet to be presented in biomedical optics. We propose a solution to this important problem based on the Karhunen-Loève expansion of the field autocorrelation function, and apply our method to the formalisms of both laser speckle contrast imaging and diffuse correlation spectroscopy

EC92-891, Farm Financial Records: Record-Keeping Alternatives For Nebraska Producers

A well organized and complete set of records is an important part of a successful farm business. Farm records are needed to prepare income tax reports, as a basis for credit, and to assist with management decisions including lease arrangements, insurance programs, cropping decisions, marketnig, and participation in government programs. Many options are available to Nebraska producers. They range from the simple hand-kept record books to fully computerized systems. A description of the major alternatives that are available to Nebraska producers follows in this publication

Urban Scale Modeling of Atmospheric Carbon Dioxide and Validation of Emission Inventories

There exists a pressing need for high resolution emissions inventories for cities. For greenhouse gases, cities and regions need a careful analysis of their carbon footprint to design effective policies to control and mitigate emissions. High resolution emissions inventories can be used in conjunction with meteorology models and atmospheric measurements to place top-down constraints on emissions. High resolution emissions inventories for criteria pollutants like NOx, CO, and O3 enable urban-scale air pollution modeling down to the neighborhood level. For example, the Vulcan project estimates CO2 using county-scale vehicle miles traveled (VMT) from the National Mobile Inventory Model (NMIM) County Database (NCD). The Hestia Project similarly allocates CO2 from Vulcan’s county-level inventory down to the building scale using eQUEST and building footprints. On-road transport is the most important sector for anthropogenic CO2, 38% in Portland, 32% nationally. Here we show a new model of CO2 emissions for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 9,352 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. EPA MOVES was used to estimate transportation CO2 emissions. Our transportation emissions served as input into WRF meteorological modeling to simulate atmospheric CO2 at sites where frequent CO2 measurements are made. We show preliminary model results

Circles, columns and screenings: mapping the institutional, discursive, physical and gendered spaces of film criticism in 1940s London

This article revisits the period considered within ‘The Quality Film Adventure: British Critics and the Cinema 1942-1948’, mapping the professional cultures, working contexts and industry relationships that underpinned the aesthetic judgements and collective directions which John Ellis has observed within the critics published writings. Drawing on the records of the Critics’ Circle, Dilys Powell’s papers and Kinematograph Weekly, it explores the evolution of increasingly organised professional cultures of film criticism and film publicity, arguing that the material conditions imposed by war caused tensions between them to escalate. In the context of two major challenges to critical integrity and practice – the evidence given by British producer R.J. Minney in front of the 1948 Royal Commission on the Press and an ongoing libel case between a BBC critic and MGM – the different spaces of hospitality and film promotion became highly contested sites. This article focuses on the ways in which these spaces were characterised, used, and policed. It finds that the value and purpose of press screenings were hotly disputed and observes the way the advancement of women within one sector (film criticism) but not the other (film publicity) created particular difficulties, as key female critics avoided the more compromised masculine spaces of publicity, making them harder for publicists to reach and fuelling trade resentment. More broadly, the article asserts the need to consider film critics as geographically and culturally located audiences, who experience films as ‘professional’ viewers within extended and embodied cultures of habitual professional practice and physical space